Expression Elements Derived From Plant Sequences Provide Effective Gene Expression Regulation and New Opportunities for Plant Biotechnology Traits.

Plant biotechnology traits provide a means to increase crop yields, manage weeds and pests, and sustainably contribute to addressing the needs of a growing population. One of the key challenges in developing new traits for plant biotechnology is the availability of expression elements for efficacious and predictable transgene regulation. Recent advances in genomics, transcriptomics, and computational tools have enabled the generation of new expression elements in a variety of model organisms. In this study, new expression element sequences were computationally generated for use in crops, starting from native Arabidopsis and maize sequences. These elements include promoters, 5' untranslated regions (5' UTRs), introns, and 3' UTRs. The expression elements were demonstrated to drive effective transgene expression in stably transformed soybean plants across multiple tissues types and developmental stages. The expressed transcripts were characterized to demonstrate the molecular function of these expression elements. The data show that the promoters precisely initiate transcripts, the introns are effectively spliced, and the 3' UTRs enable predictable processing of transcript 3' ends. Overall, our results indicate that these new expression elements can recapitulate key functional properties of natural sequences and provide opportunities for optimizing the expression of genes in future plant biotechnology traits.

PHENIX: a comprehensive Python-based system for macromolecular structure solution.

Macromolecular X-ray crystallography is routinely applied to understand biological processes at a molecular level. However, significant time and effort are still required to solve and complete many of these structures because of the need for manual interpretation of complex numerical data using many software packages and the repeated use of interactive three-dimensional graphics. PHENIX has been developed to provide a comprehensive system for macromolecular crystallographic structure solution with an emphasis on the automation of all procedures. This has relied on the development of algorithms that minimize or eliminate subjective input, the development of algorithms that automate procedures that are traditionally performed by hand and, finally, the development of a framework that allows a tight integration between the algorithms.

MolProbity: all-atom contacts and structure validation for proteins and nucleic acids.

MolProbity is a general-purpose web server offering quality validation for 3D structures of proteins, nucleic acids and complexes. It provides detailed all-atom contact analysis of any steric problems within the molecules as well as updated dihedral-angle diagnostics, and it can calculate and display the H-bond and van der Waals contacts in the interfaces between components. An integral step in the process is the addition and full optimization of all hydrogen atoms, both polar and nonpolar. New analysis functions have been added for RNA, for interfaces, and for NMR ensembles. Additionally, both the web site and major component programs have been rewritten to improve speed, convenience, clarity and integration with other resources. MolProbity results are reported in multiple forms: as overall numeric scores, as lists or charts of local problems, as downloadable PDB and graphics files, and most notably as informative, manipulable 3D kinemage graphics shown online in the KiNG viewer. This service is available free to all users at http://molprobity.biochem.duke.edu.

The backrub motion: how protein backbone shrugs when a sidechain dances.

Surprisingly, the frozen structures from ultra-high-resolution protein crystallography reveal a prevalent, but subtle, mode of local backbone motion coupled to much larger, two-state changes of sidechain conformation. This "backrub" motion provides an influential and common type of local plasticity in protein backbone. Concerted reorientation of two adjacent peptides swings the central sidechain perpendicular to the chain direction, changing accessible sidechain conformations while leaving flanking structure undisturbed. Alternate conformations in sub-1 angstroms crystal structures show backrub motions for two-thirds of the significant Cbeta shifts and 3% of the total residues in these proteins (126/3882), accompanied by two-state changes in sidechain rotamer. The Backrub modeling tool is effective in crystallographic rebuilding. For homology modeling or protein redesign, backrubs can provide realistic, small perturbations to rigid backbones. For large sidechain changes in protein dynamics or for single mutations, backrubs allow backbone accommodation while maintaining H bonds and ideal geometry.

MOLPROBITY: structure validation and all-atom contact analysis for nucleic acids and their complexes.

MolProbity is a general-purpose web service offering quality validation for three-dimensional (3D) structures of proteins, nucleic acids and complexes. It provides detailed all-atom contact analysis of any steric problems within the molecules and can calculate and display the H-bond and van der Waals contacts in the interfaces between components. An integral step in the process is the addition and full optimization of all hydrogen atoms, both polar and nonpolar. The results are reported in multiple forms: as overall numeric scores, as lists, as downloadable PDB and graphics files, and most notably as informative, manipulable 3D kinemage graphics shown on-line in the KiNG viewer. This service is available free to all users at http://kinemage.biochem.duke.edu.

Structure validation by Calpha geometry: phi,psi and Cbeta deviation.

Geometrical validation around the Calpha is described, with a new Cbeta measure and updated Ramachandran plot. Deviation of the observed Cbeta atom from ideal position provides a single measure encapsulating the major structure-validation information contained in bond angle distortions. Cbeta deviation is sensitive to incompatibilities between sidechain and backbone caused by misfit conformations or inappropriate refinement restraints. A new phi,psi plot using density-dependent smoothing for 81,234 non-Gly, non-Pro, and non-prePro residues with B < 30 from 500 high-resolution proteins shows sharp boundaries at critical edges and clear delineation between large empty areas and regions that are allowed but disfavored. One such region is the gamma-turn conformation near +75 degrees,-60 degrees, counted as forbidden by common structure-validation programs; however, it occurs in well-ordered parts of good structures, it is overrepresented near functional sites, and strain is partly compensated by the gamma-turn H-bond. Favored and allowed phi,psi regions are also defined for Pro, pre-Pro, and Gly (important because Gly phi,psi angles are more permissive but less accurately determined). Details of these accurate empirical distributions are poorly predicted by previous theoretical calculations, including a region left of alpha-helix, which rates as favorable in energy yet rarely occurs. A proposed factor explaining this discrepancy is that crowding of the two-peptide NHs permits donating only a single H-bond. New calculations by Hu et al. [Proteins 2002 (this issue)] for Ala and Gly dipeptides, using mixed quantum mechanics and molecular mechanics, fit our nonrepetitive data in excellent detail. To run our geometrical evaluations on a user-uploaded file, see MOLPROBITY (http://kinemage.biochem.duke.edu) or RAMPAGE (http://www-cryst.bioc.cam.ac.uk/rampage).

Scientific benchmarks for guiding macromolecular energy function improvement.

Accurate energy functions are critical to macromolecular modeling and design. We describe new tools for identifying inaccuracies in energy functions and guiding their improvement, and illustrate the application of these tools to the improvement of the Rosetta energy function. The feature analysis tool identifies discrepancies between structures deposited in the PDB and low-energy structures generated by Rosetta; these likely arise from inaccuracies in the energy function. The optE tool optimizes the weights on the different components of the energy function by maximizing the recapitulation of a wide range of experimental observations. We use the tools to examine three proposed modifications to the Rosetta energy function: improving the unfolded state energy model (reference energies), using bicubic spline interpolation to generate knowledge-based torisonal potentials, and incorporating the recently developed Dunbrack 2010 rotamer library (Shapovalov & Dunbrack, 2011).

POWRS: position-sensitive motif discovery.

UNLABELLED: Transcription factors and the short, often degenerate DNA sequences they recognize are central regulators of gene expression, but their regulatory code is challenging to dissect experimentally. Thus, computational approaches have long been used to identify putative regulatory elements from the patterns in promoter sequences. Here we present a new algorithm "POWRS" (POsition-sensitive WoRd Set) for identifying regulatory sequence motifs, specifically developed to address two common shortcomings of existing algorithms. First, POWRS uses the position-specific enrichment of regulatory elements near transcription start sites to significantly increase sensitivity, while providing new information about the preferred localization of those elements. Second, POWRS forgoes position weight matrices for a discrete motif representation that appears more resistant to over-generalization. We apply this algorithm to discover sequences related to constitutive, high-level gene expression in the model plant Arabidopsis thaliana, and then experimentally validate the importance of those elements by systematically mutating two endogenous promoters and measuring the effect on gene expression levels. This provides a foundation for future efforts to rationally engineer gene expression in plants, a problem of great importance in developing biotech crop varieties. AVAILABILITY: BSD-licensed Python code at http://grassrootsbio.com/papers/powrs/.

High-throughput imaging and analysis of root system architecture in Brachypodium distachyon under differential nutrient availability.

Nitrogen (N) and phosphorus (P) deficiency are primary constraints for plant productivity, and root system architecture (RSA) plays a vital role in the acquisition of these nutrients. The genetic determinants of RSA are poorly understood, primarily owing to the complexity of crop genomes and the lack of sufficient RSA phenotyping methods. The objective of this study was to characterize the RSA of two Brachypodium distachyon accessions under different nutrient availability. To do so, we used a high-throughput plant growth and imaging platform, and developed software that quantified 19 different RSA traits. We found significant differences in RSA between two Brachypodium accessions grown on nutrient-rich, low-N and low-P conditions. More specifically, one accession maintained axile root growth under low N, while the other accession maintained lateral root growth under low P. These traits resemble the RSA of crops adapted to low-N and -P conditions, respectively. Furthermore, we found that a number of these traits were highly heritable. This work lays the foundation for future identification of important genetic components of RSA traits under nutrient limitation using a mapping population derived from these two accessions.

ROSETTA3: an object-oriented software suite for the simulation and design of macromolecules.

We have recently completed a full re-architecturing of the ROSETTA molecular modeling program, generalizing and expanding its existing functionality. The new architecture enables the rapid prototyping of novel protocols by providing easy-to-use interfaces to powerful tools for molecular modeling. The source code of this rearchitecturing has been released as ROSETTA3 and is freely available for academic use. At the time of its release, it contained 470,000 lines of code. Counting currently unpublished protocols at the time of this writing, the source includes 1,285,000 lines. Its rapid growth is a testament to its ease of use. This chapter describes the requirements for our new architecture, justifies the design decisions, sketches out central classes, and highlights a few of the common tasks that the new software can perform.

RosettaLigand docking with full ligand and receptor flexibility.

Computational docking of small-molecule ligands into protein receptors is an important tool for modern drug discovery. Although conformational adjustments are frequently observed between the free and ligand-bound states, the conformational flexibility of the protein is typically ignored in protein-small molecule docking programs. We previously described the program RosettaLigand, which leverages the Rosetta energy function and side-chain repacking algorithm to account for flexibility of all side chains in the binding site. Here we present extensions to RosettaLigand that incorporate full ligand flexibility as well as receptor backbone flexibility. Including receptor backbone flexibility is found to produce more correct docked complexes and to lower the average RMSD of the best-scoring docked poses relative to the rigid-backbone results. On a challenging set of retrospective and prospective cross-docking tests, we find that the top-scoring ligand pose is correctly positioned within 2 A RMSD for 64% (54/85) of cases overall.

Blind docking of pharmaceutically relevant compounds using RosettaLigand.

It is difficult to properly validate algorithms that dock a small molecule ligand into its protein receptor using data from the public domain: the predictions are not blind because the correct binding mode is already known, and public test cases may not be representative of compounds of interest such as drug leads. Here, we use private data from a real drug discovery program to carry out a blind evaluation of the RosettaLigand docking methodology and find that its performance is on average comparable with that of the best commercially available current small molecule docking programs. The strength of RosettaLigand is the use of the Rosetta sampling methodology to simultaneously optimize protein sidechain, protein backbone and ligand degrees of freedom; the extensive benchmark test described here identifies shortcomings in other aspects of the protocol and suggests clear routes to improving the method.

KING (Kinemage, Next Generation): a versatile interactive molecular and scientific visualization program.

Proper visualization of scientific data is important for understanding spatial relationships. Particularly in the field of structural biology, where researchers seek to gain an understanding of the structure and function of biological macromolecules, it is important to have access to visualization programs which are fast, flexible, and customizable. We present KiNG, a Java program for visualizing scientific data, with a focus on macromolecular visualization. KiNG uses the kinemage graphics format, which is tuned for macromolecular structures, but is also ideal for many other kinds of spatially embedded information. KiNG is written in cross-platform, open-source Java code, and can be extended by end users through simple or elaborate "plug-in" modules. Here, we present three such applications of KiNG to problems in structural biology (protein backbone rebuilding), bioinformatics of high-dimensional data (e.g., protein sidechain chi angles), and classroom education (molecular illustration). KiNG is a mature platform for rapidly creating and capitalizing on scientific visualizations. As a research tool, it is invaluable as a test bed for new methods of visualizing scientific data and information. It is also a powerful presentation tool, whether for structure browsing, teaching, direct 3D display on the web, or as a method for creating pictures and videos for publications. KiNG is freely available for download at http://kinemage.biochem.duke.edu.

KinImmerse: Macromolecular VR for NMR ensembles.

BACKGROUND: In molecular applications, virtual reality (VR) and immersive virtual environments have generally been used and valued for the visual and interactive experience - to enhance intuition and communicate excitement - rather than as part of the actual research process. In contrast, this work develops a software infrastructure for research use and illustrates such use on a specific case. METHODS: The Syzygy open-source toolkit for VR software was used to write the KinImmerse program, which translates the molecular capabilities of the kinemage graphics format into software for display and manipulation in the DiVE (Duke immersive Virtual Environment) or other VR system. KinImmerse is supported by the flexible display construction and editing features in the KiNG kinemage viewer and it implements new forms of user interaction in the DiVE. RESULTS: In addition to molecular visualizations and navigation, KinImmerse provides a set of research tools for manipulation, identification, co-centering of multiple models, free-form 3D annotation, and output of results. The molecular research test case analyzes the local neighborhood around an individual atom within an ensemble of nuclear magnetic resonance (NMR) models, enabling immersive visual comparison of the local conformation with the local NMR experimental data, including target curves for residual dipolar couplings (RDCs). CONCLUSION: The promise of KinImmerse for production-level molecular research in the DiVE is shown by the locally co-centered RDC visualization developed there, which gave new insights now being pursued in wider data analysis.

A test of enhancing model accuracy in high-throughput crystallography.

The high throughput of structure determination pipelines relies on increased automation and, consequently, a reduction of time spent on interactive quality control. In order to meet and exceed current standards in model accuracy, new approaches are needed for the facile identification and correction of model errors during refinement. One such approach is provided by the validation and structure-improvement tools of the MOL: PROBITY: web service. To test their effectiveness in high-throughput mode, a large subset of the crystal structures from the SouthEast Collaboratory for Structural Genomics (SECSG) has used protocols based on the MOL: PROBITY: tools. Comparison of 29 working-set and 19 control-set SECSG structures shows that working-set outlier scores for updated Ramachandran-plot, sidechain rotamer, and all-atom steric criteria have been improved by factors of 5- to 10-fold (relative to the control set or to a Protein Data Bank sample), while quality of covalent geometry, R(work), R(free), electron density and difference density are maintained or improved. Some parts of this correction process are already fully automated; other parts involve manual rebuilding of conformations flagged by the tests as trapped in the wrong local minimum, often altering features of functional significance. The ease and effectiveness of this technique shows that macromolecular crystal structures from either traditional or high-throughput determinations can feasibly reach a new level of excellence in conformational accuracy and reliability.